www.elsevier.com/locate/dss

Decision Support Systems

Value-based Adoption of Mobile Internet:

An empirical investigation

Hee-Woong Kim *, Hock Chuan Chan, Sumeet Gupta

Department of Information Systems, National University of Singapore, S16 #05-08, 3 Science Drive 2, Singapore 117543, Singapore

Available online 14 July 2005

Abstract

This study examines the adoption of Mobile Internet (M-Internet) as a new Information and Communication Technology

(ICT) from the value perspective. M-Internet is a fast growing enabling technology for Mobile Commerce. However, despite its

phenomenal growth and although M-Internet essentially provides the same services as stationary Internet, its adoption rate in

many countries is very low compared to that of stationary Internet. The well-known Technology Adoption Model (TAM) has

been used for explaining the adoption of traditional technologies. Most adopters and users of traditional technologies (e.g.,

spreadsheet, word processor) are employees in an organizational setting who use the technology for work purposes, and the cost

of mandatory adoption and usage is borne by the organization. In contrast, adopters and users of M-Internet are individuals who

play the dual roles of technology user and service consumer. Most of them adopt and use it for personal purposes, and the cost

of voluntary adoption and usage is borne by the individuals. Thus, the adopters of new ICT, especially M-Internet, are also

consumers rather than simply technology users. By adopting the theory of consumer choice and decision making from

economics and marketing research, this study develops the Value-based Adoption Model (VAM) and explains customers’

M-Internet adoption from the value maximization perspective. The findings demonstrate that consumers’ perception of the

value of M-Internet is a principal determinant of adoption intention, and the other beliefs are mediated through perceived value.

The theoretical and practical implications of VAM related to M-Internet are discussed.

D 2005 Elsevier B.V. All rights reserved.

Keywords: Mobile Internet; Value-based Adoption Model; Technology Adoption Model

1. Introduction

With the rapid adoption of the Internet and elec-

tronic commerce (e-commerce), the acclimatization of

0167-9236/$ - see front matter D 2005 Elsevier B.V. All rights reserved.

doi:10.1016/j.dss.2005.05.009

* Corresponding author. Tel.: +65 6874 4867.

E-mail addresses: kimhw@comp.nus.edu.sg (H.-W. Kim),

chanhc@comp.nus.edu.sg (H.C. Chan), g0202136@nus.edu.sg

(S. Gupta).

consumers to mobile devices, and the advent of third

generation (3G) technology, Mobile Commerce (M-

Commerce) is set to become one of the most promis-

ing and lucrative growth markets. 3G technology,

which started in Japan in 2001, supports rich media

such as video clips whereas only text is supported by

second generation (2G) technology [53]. According to

the Ministry of Posts and Telecommunications of

Japan, the Japanese M-Commerce market is expected

43 (2007) 111–126

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126112

to expand to 1.1 trillion yen (US$9.4 billion) in FY

2005 [39]. The main reason for this rapid growth of

M-Commerce is the rapid adoption of Mobile Internet

(M-Internet) as a medium of communication, contents

service and commerce, which has in turn come about

as Japanese mobile service providers adopt 3G tech-

nology. As the growth of M-Commerce is closely

linked to that of M-Internet, a clear and comprehen-

sive understanding of M-Internet adoption is therefore

essential to understanding M-Commerce adoption. As

an initial step toward understanding customer behav-

ior related to M-Commerce, this study examines the

adoption of M-Internet.

In Japan, the number of people usingM-Internet has

already exceeded those using stationary Internet [57].

The growth of the M-Internet market has been estimat-

ed to grow from $272 billion in 2000 to $2600 billion

in 2004. Despite its phenomenal growth, M-Internet is

still in its infancy in most countries. Accordingly,

research in M-Internet has been limited, although the

subject is fast gaining interest in the information sys-

tems research community. Previous research has main-

ly focused on technological developments (e.g.,

[7,51]), overlooking users’ perspective of M-Internet

[34]. Only a few studies [2] have explored how indi-

viduals use M-Internet and the factors influencing its

adoption. Although the information technology (IT)

adoption literature is rich in studies on factors of

technology adoption, the technologies being studied

are most often business software applications, email

systems and personal productivity applications. Con-

ventional adoption models have been extended and

modified by some researchers to explain the adoption

of telecommunication-oriented services like telemedi-

cine [28] and mobile telephones [35] because conven-

tional theories in their original forms are inadequate

when explaining the adoption of such technologies.

The most prominent model employed to explain the

adoption and usage of technology by individuals is the

Technology Adoption Model (TAM) [15]. Based on

the Theory of Reasoned Action, TAM is a parsimoni-

ous model, asserting that all influences of external

variables such as system design features on behavior

are mediated by Usefulness and Ease of Use. TAM

was originally developed to explain individuals’ adop-

tion of traditional technology (e.g., Spreadsheet, email,

Software development tools) in an organizational set-

ting. However, TAM has its limitations in explaining

the adoption of new Information and Communication

Technology (ICT) such as M-Internet. Most adopters

and users of traditional technologies are employees in

an organizational setting, where they use the technol-

ogy for work purposes, and the cost of mandatory

adoption and usage is borne by the organization. In

contrast, adopters and users of new ICT are individuals

who play the dual roles of technology user and service

consumer. Most of them adopt and use the new ICT for

personal purposes, and the cost of voluntary adoption

and usage is borne by the individuals. For example,

one of the major issues in adopting and using M-

Internet is monetary cost, such as usage fee. Potential

adopters of M-Internet are mobile service consumers

who will consider prices and evaluate M-Internet

based on its benefits and costs. Thus, the adopters of

new ICT, especially M-Internet, are consumers rather

than simply technology users.

Our research aims to examine M-Internet adoption

as a new ICT from the consumer perspective, and not

just from the technology user perspective. A number of

studies exist on consumer choice and decision making

in the economics [31,40] and marketing literature

[6,12,33,52,61]. The basic and common assumption

in examining consumer behavior is value maximiza-

tion. For example, the prospect theory [31] was pro-

posed to explain the choices made by individual

customers. In this theory, the value function is adopted

and defined over perceived gain or loss relative to a

reference point. It basically proposes that people

choose the behavior that leads to the highest payoff.

The principles of cost–benefit analyses are exem-

plified in the concept of value, which is broadly

defined as the trade-off between total benefits re-

ceived and total sacrifices. A value-based model

would be able to capture the monetary sacrifice ele-

ment and present adoption as a comparison of benefits

and costs. We propose and empirically test a Value-

based Adoption Model (VAM) of M-Internet by inte-

grating the most relevant findings of the technology

adoption and value literature. This combined frame-

work represents a novel approach to understanding

consumers’ adoption of mobile technology. Our find-

ings should help in the theoretical understanding of

the adoption behavior of individual consumers in a

voluntary and personal context. In practice, our find-

ings could guide mobile service developers in aug-

menting their offerings.

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126 113

The paper is structured as follows. In Section 2, a

literature review on perceived value and its relevance

to this study is presented. In Section 3, we propose our

research model and hypotheses based on the literature

review. Section 4 describes the research methodology

followed by results and discussion in Sections 5 and 6,

respectively. In Section 7 we discuss the theoretical and

practical implications of our research; we also high-

light opportunities for future research in the section.

Section 8 concludes the paper with a brief summary.

2. Conceptual background

2.1. Mobile Internet and Mobile Commerce

Mobile Commerce, also known as M-Commerce,

is basically any e-commerce done in a wireless envi-

ronment, especially via the Internet [53]. The major

characteristics of M-Commerce that differentiate it

from other forms of e-commerce are mobility and

reach. Users can initiate real-time contact with com-

mercial and other systems wherever they happen to be

(mobility). With M-Commerce, people can be reached

at any time (reach).

Mobile Internet is an enabling technology for M-

Commerce. M-Commerce uses radio-based wireless

devices to conduct business transactions over the

Web-based e-commerce system [45]. Mobile devices

create an opportunity to deliver new services to exist-

ing customers and attract new ones. M-Commerce

began with analog based first-generation wireless

(1G) technology in 1979, which was gradually

replaced in the early 1990s with second generation

(2G) digital radio technology which could accommo-

date text. Third generation (3G) technology support-

ing rich media such as video clips began in 2001 in

Japan, and is currently proliferating at a fast pace.

Between 3G and 2G is 2.5G, an interim technology

based on GPRS and EDGE that can accommodate

limited graphics. In Singapore, WAP and GPRS tech-

nology are offered by mobile service providers like

Singtel, M1 and StarHub. GPRS is a radio technology

for GSM networks that adds packet-switching proto-

cols, allows a shorter set-up time for ISP connections,

and offers the possibility for service providers to

charge customers by the amount of data sent rather

than connect time. GPRS is a 2.5G enhancement to

GSM, and is the most significant step toward 3G,

needing a similar business model, and service and

network architectures.

Although M-Internet essentially provides the same

services as stationary Internet, its adoption rate in

many countries is very low compared to that of sta-

tionary Internet. The services offered by M-Internet

can be categorized into 3Cs—Commerce, Communi-

cation and Contents. Commerce ranges from mobile

banking and e-ticketing to physical product purchases

while email and interactive services such as Yahoo!

Chat are considered communication services. Con-

tents include downloads, news, traffic/stock updates

and other time-sensitive, location-based services.

2.2. Previous research on value

Value is emphasized in the field of economics, and

it has its foundation in exchange, utility and labor

value theories, as well as in marketing, accounting

and finance, while also having roots in psychology

and social psychology. Researchers have come up

with many different terms to describe value, generally

differentiating by context the same basic concept:

consumption value [44], acquisition and transaction

value [52], service value, customer value [60], con-

sumer value [27] and perceived value [61].

From the utilitarian perspective, customer value

perceptions are a combination of the acquisition

value and transaction value of the product [52].

Some studies have differentiated between overall

value, acquisition value and transaction value

[25,52], but since the same definition and measure-

ments have been applied to both acquisition value and

overall value in most studies, we will use only an

overall value term without any specific reference to

acquisition value. Modeling the perceived value of a

product solely on price is an important but insufficient

conceptualization because most of the time, customers

consider attributes other than price, such as perceived

quality of the product. Early interpretations of the

benefit and sacrifice components center on perceived

quality and monetary price [11,22,25]. These simplis-

tic trade-off models ignore the multi-dimensionality of

decision making and do not fully represent perceived

benefits and sacrifices.

Appreciating that value not only has a functional

aspect, several typologies of value have been pro-

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126114

posed. Sheth et al. [44] explained consumption in

terms of functional value, social value, emotional

value, epistemic value and conditional value. Any,

or all, of the five consumption values may influence

consumption experience, depending on the situation.

Holbrook [27] proposed a typology of perceived value

which includes eight types of value: convenience,

quality, success, reputation, fun, beauty, virtue and

faith. Both typologies are comprehensive in explain-

ing the benefits customers get from consumption but

they fail to take into account the costs associated with

consumption.

Zeithaml’s [61] definition of perceived value is the

most widely accepted, according to which a consu-

mer’s perceptions of what is received and what is

Table 1

Previous research on perceived value

Reference Context Content

Zeithaml [61] Product (beverages) Research

Benefit components

Sacrifice components

Dodds et al. [22] Product (calculator,

stereo headset player)

Research

Benefit components

Sacrifice components

Kerin et al. [33] Service (electric utility) Research

Benefit components

Sacrifice components

Chang and

Wildt [11]

Product

(apartment and PCs)

Research

Benefit components

Sacrifice components

Sweeney et al. [49] Retail environment

(electrical appliances)

Research

Benefit components

Sacrifice components

DeSarbo et al. [20] Service (electric utility) Research

Benefit components

Sacrifice components

Sweeney and

Soutar [48]

Product (durable goods) Research

Benefit components

Sacrifice components

Petrick [42] Service (cruise) Research

Benefit components

Sacrifice components

Baker et al. [6] Retail environment

(cards and gifts)

Research

Benefit components

Sacrifice components

Chen and

Dubinsky [12]

E-commerce

environment

Research

Benefit components

Sacrifice components

given determine the consumer’s overall assessment

of the utility of a product. Table 1 presents the select-

ed studies on perceived value with the benefit and

sacrifice components over diverse contexts. We refer

to the perceived value of M-Internet in this paper as a

consumer’s overall perception of M-Internet based on

the considerations of its benefits and sacrifices needed

to acquire and/or use it. The following section

explains the role of perceived value in explaining

technology adoption.

2.3. Using perceived value to explain adoption

In justifying the constructs of perceived usefulness

and ease of use in TAM, Davis [15] cited theories

Finding the antecedents of purchase behavior

Intrinsic and extrinsic product attributes, perceived quality and

other high level abstractions

Perceived monetary price and perceived non-monetary price

Finding the antecedents of willingness to buy

Perceived quality

Perceived price (having a curvilinear relationship to

perceived value)

Finding the antecedents of perceived store value

Perceived merchandise quality, perceived shopping experience

Perceived merchandise price

Finding the antecedents of purchase intentions

Quality

Price

Finding the antecedents of willingness to buy

Technical service quality and product quality

Relative price

Finding the antecedents of perceived value

Perceived quality

Perceived price

Finding the antecedents of willingness to buy, willingness to

recommend and not expecting problems with product

Quality (functional value), emotional value, social value

Price (functional value)

Finding the antecedents of repurchase intentions and word

of mouth

Emotional response, quality and reputation

Behavioral price and monetary price

Finding the antecedents of store patronage intentions

Merchandise quality perceptions

Monetary price perceptions

Finding the antecedents of purchase intention

Perceived product quality and valence of experience

Perceived risk and product price

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126 115

from multiple disciplinary domains. Of significance is

the cost–benefit paradigm from behavioral decision

theory [30] which explains an individual’s choice

among various decision-making strategies as a cogni-

tive trade-off between the effort required to employ

the strategy (i.e., ease of use) and the quality (i.e.,

usefulness) of the resulting decision [15]. That rela-

tionship is analogous to the definition of perceived

value in this study. Perceived value is treated as a

trade-off between the bgiveQ and bgetQ components of

a product [21]. According to [61], perceived value is

the consumer’s overall assessment of the utility of a

product based on perceptions of what is received and

what is given. From the consumer choice perspective,

consumers estimate the value of the choice object by

considering all relevant benefit and sacrifice factors

[31,40,52,61]. Value represents an overall estimation

of the choice object. Based on this overall estimation,

consumers decide their choice behavior.

In contrast, TAM has no construct which represents

an overall estimation of the adoption object. It

explains adoption behavior only with two factors:

usefulness and ease of use. There have been some

attempts to incorporate attitude into TAM. Attitude is

a psychological tendency that is expressed by evalu-

ating a particular entity with some degree of bfavor ordisfavorQ [24]. However, Davis et al. [16] omitted

attitude in the final TAM due to its weak mediation

of beliefs on adoption intention. Empirical studies

have found that attitude does not influence intention

directly [56], and that TAM retains its robustness even

without including attitude [16,55]. Venkatesh et al.

[56] concluded in their review of IT acceptance re-

PerceiValu

Benefit

Sacrifice

Usefulness

Technicality

Perceived Fee

EnjoymentH1

H2

H3

H4

Fig. 1. Value based adoption

search that attitudinal constructs are significant only

when specific cognitions (performance and effort ex-

pectancies) are not included in the model.

3. Research model and hypotheses

Taking into account our previous arguments, we

develop a Value-based Adoption Model (VAM) of M-

Internet, as shown in Fig. 1. We strive to achieve

parsimony by capturing a small number of factors

that account for most of the variance in adoption

intention, so that it would be easy and straightforward

to predict M-Internet adoption.

3.1. Perceived benefits

The Cognitive Evaluation Theory [18] classifies

motivations into extrinsic and intrinsic subsystems.

Extrinsic motivation refers to the performance of an

activity to achieve a specific goal (e.g., rewards) while

intrinsic motivation refers to the performance of an

activity for no apparent reinforcement other than the

process of performing the activity per se [16]. Both

extrinsic and intrinsic factors have been found to

influence perceived value and behavioral intention

[43], and these findings also apply to information

systems [38]. It has also been suggested that custo-

mers’ evaluation of a product includes both cognitive

and affective elements [23], and that products are

purchased for their utilitarian and hedonic benefits

[4]. For this reason, we propose usefulness and enjoy-

ment as the benefit components of perceived value.

vede

AdoptionIntention

H5

model of technology.

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126116

3.1.1. Extrinsic and cognitive benefit: usefulness

Usefulness is defined as the total value a user

perceives from using a new technology [43]. The

motivation-oriented perspective of TAM views per-

ceived usefulness as outcome expectancy and a mea-

sure of extrinsic motivation [55]. Individuals evaluate

the consequences of their behavior in terms of per-

ceived usefulness and base their choice of behavior on

the desirability of the usefulness. Performance expec-

tancies such as perceived usefulness, which focuses

on task accomplishment [56], reflect the desire of an

individual to engage in an activity because of external

rewards.

The construct of usefulness is akin to the marketing

concept of product quality, which is defined as the

customer’s cognitive assessment of the excellence or

superiority of a product [61]. The customer believes

that the product’s attributes denote some desirable

functions that it can perform. Steenkamp [47] defines

product quality as fitness for consumption, i.e., the

product’s usefulness in serving the consumer’s needs.

Researchers have proven that product quality has a

positive effect on perceived value [22], and we expect

usefulness to affect perceived value in the same way.

The usefulness construct has been used extensively

in information systems and technology research, and

has strong empirical support as an important predictor

of technology adoption (e.g., [36,50]). According to

Pedersen et al. [41], the usefulness of M-Internet

services affects their adoption, underlining the factor

as a key one in M-Internet adoption. We therefore

hypothesize:

H1. Usefulness is positively related to perceived

value.

3.1.2. Intrinsic and affective benefit: enjoyment

Individuals, who experience immediate pleasure or

joy from using a technology and perceive any activity

involving the technology to be personally enjoyable in

its own right aside from the instrumental value of the

technology, are more likely to adopt the technology

and use it more extensively than others [16]. This

notion is in line with popular definitions of emotional

value. Sweeney and Soutar [48] defined emotional

value as the utility derived from feelings or affective

states that a product generates. Enjoyment refers to the

extent to which the activity of using a product is

perceived to be enjoyable in its own right, apart

from any performance consequences that may be

anticipated [17]. Enjoyment thus represents an affec-

tive and intrinsic benefit.

Petrick [42] characterized what customers

breceiveQ as emotional response/joy received from

purchase and product quality. Past researches have

also shown that the benefit component comprises

perceived enjoyment, in addition to perceived useful-

ness [48], and that enjoyment and fun have a signif-

icant effect on technology acceptance beyond

usefulness [16]. We therefore hypothesize:

H2. Enjoyment is positively related to perceived

value.

3.2. Perceived sacrifices

Perceived sacrifices are both monetary and non-

monetary [52,61]. Monetary spending includes the

actual price of the product, and it is generally mea-

sured based on customers’ perceptions of the actual

price paid. Non-monetary costs usually include time,

effort and other unsatisfactory spending for the pur-

chase and consumption of the product. Several ex-

ploratory surveys have identified technical factors and

price as the most significant barrier to M-Internet

adoption [3,59]. For this reason, we propose the tech-

nicality of M-Internet and perceived fee to be the

sacrifice components of perceived value.

3.2.1. Non-monetary sacrifice: technicality

We adapted DeLone and McLean’s [19] definition

of system quality and define technicality as the degree

to which M-Internet is perceived as being technically

excellent in the process of providing services. The

technicality of M-Internet is determined by users’

perceptions of ease of use (whether using the system

is free of physical, mental and learning effort [15]),

system reliability (whether the system is error-free,

consistently available and secure), connectivity

(whether connection is instant and straightforward)

and efficiency (whether loading and response time is

short).

Ease of use has been widely used as an element of

technicality. It is defined as bthe degree to which an

individual believes that using a particular system

would be free of physical and mental effortQ [15]. In

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126 117

this study, ease of use refers to the overall user-friend-

liness of using mobile devices to access the Internet.

In expectancy value models such as TAM, effort is

considered a component of cost; it therefore follows

that ease of use is a sacrifice in M-Internet adoption.

Cronin et al. [14] found that excessive mental cost

affects perceived overall cost to the user. Ease of use

is an important issue for M-Internet. This is because

M-Internet runs on limited resources compared to

other systems, especially for users of mobile phone

where screen size and manipulation difficulty demand

mental and physical efforts. Additionally, ease of use

has been found to be a more significant factor for new

adopters than experienced users [56]. Specifically, it

has been shown that the complexity of the innovation

has a significant negative relationship with the adop-

tion of the new application (e.g., [43]).

As the characteristics of M-Internet have not been

fully modeled in existing information systems re-

search, other elements of technicality have to be con-

sidered as the entire experience will contribute to

customers’ evaluation of the technology. This is

very true in today’s context as customers are increas-

ingly demanding in terms of system and service ex-

cellence. Non-monetary costs include time costs,

search/effort costs, convenience costs and psycholog-

ical costs [61]. In an M-Internet environment, loading

and response time can be considered time costs while

ease of use and connectivity are considered effort and

convenience cost, respectively. Psychological factors

include inner conflict, frustration, depression, discom-

fort, anxiety, tension, annoyance, mental fatigue, etc.

[9]. Technicality of the system is a combination of all

the non-monetary costs. We therefore hypothesize:

H3. Technicality is negatively related to perceived

value.

3.2.2. Monetary sacrifice: perceived fee

Perceived price symbolizes the encoding or inter-

nalization of the objective selling price of a product/

service [29]. The fee structure of M-Internet consists

of the pay-as-you-use scheme and subscription-based

pricing. Without any experience with new technolo-

gies such as M-Internet, customers cannot judge

whether the fee quoted to them is high or low. Accord-

ing to the Adaptation Level theory, instead of having

perfect information about prices, customers possess

internal reference prices and make comparison with

these prices [25]. In the case of M-Internet, customers

would probably compare the fee of M-Internet usage

with previously encoded prices of mobile phone calls

and stationary Internet access. The result of this com-

parison forms the customers’ perception of the fee.

Complementing the Adaptation Level theory, the

Assimilation-Contrast theory suggests that a stimulus

value close to the internal reference price is assimilat-

ed with that price while one too far from the reference

is contrasted. Andersson and Heinonen [3] found that

young customers’ perceptions of M-Internet are af-

fected when they compare mobile services with sta-

tionary Internet services, which are mostly provided

free.

It has been proposed that perceived fee directly

influences perceived value [11,22,52,61]. Studies in

marketing show that perceived monetary price and

perceived value are negatively related [11]. Therefore,

we propose a negative perceived fee-overall perceived

value relationship, i.e., higher fee perceptions are

associated with lower value perceptions. We therefore

hypothesize:

H4. Perceived fee is negatively related to perceived

value.

3.3. Adoption intention

According to the economic theory of utility, cus-

tomers try to achieve maximum utility or satisfaction,

given their resource limitations. Our definition of

perceived value reflects this by comparing benefits

with sacrifices and is therefore an indicator of adop-

tion intention. On the other hand, Thaler’s [52] model

of consumer choice is a combination of economic

reasoning and cognitive psychology. The value func-

tion is psychologically based and replaces the utility

function from economics theory. The central principle

of value function is that it is defined over perceived

gains and losses relative to some natural reference

point, suggesting that people tend to respond to cog-

nitive comparisons rather than absolute levels, and

that it is steeper for losses than for gains, signifying

that sacrifices hurt more than the pleasure given by the

benefits. Urbany et al. [54] proved that transaction

utility is a predictor of purchase intention and behav-

ior. The relationship between perceived value and

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126118

adoption intention has never been examined before,

but there is strong empirical support that perceived

value affects perceptual intention to use [49]. We

therefore hypothesize:

H5. Perceived value is positively related to adoption

intention.

Table 2

Descriptive statistics of the respondents’ characteristics

Measure Items Subjects

Frequency Percentage

Gender Female 40 24.8

Male 121 75.2

Age 20–29 142 88.2

30–39 19 11.8

Job Student 87 54.0

Professional 62 38.5

Self-employed 3 1.9

Others 9 5.6

Usage experience 1–2 times 71 27.2

3–4 times 63 39.1

z5 times 27 16.7

Mobile device Mobile phone 148 91.9

PDA 13 18.1

M-Internet servicesa Communications 36 22.4

Contents 64 39.7

Commerce 61 37.9

Total 161 100.0

a Most frequently tried.

4. Research methodology

This study has either adopted or adapted extant

validated scales and experimental procedures wherev-

er possible. Where items have been developed, we

have followed strict procedures. All measurements

have been further checked for reliability and validity,

as we will report later. We adopted the construct of

adoption intention from Agarwal and Karahanna [1].

For perceived value, we adapted the construct from

Sirdeshmukh et al. [46]. Since perceived value means

the comparison between cost and benefit, our con-

struct compares (1) fee and value, (2) effort and

benefit, and (3) time spent being worthwhile and

overall good value. Usefulness was adopted from

Davis [15] and enjoyment was adopted from Agarwal

and Karahanna [1]. Perceived fee was adapted from

Voss et al. [58]. In developing the new construct,

technicality, we followed standard psychometric

scale development procedures [5]. First, the domain

of the construct was specified. Second, the items were

developed based on the conceptual definition. Third,

the items were refined on the basis of extensive pret-

ests of the survey instrument. Thus, technicality was

developed by considering the items of system quality

from DeLone and McLean [19]: bconnected instantlyQ,btakes a short time to respondQ, beasy to get the M-

Internet to do what I want to doQ, and breliableQ. Allitems were measured on a seven-point Likert scale.

Two information systems researchers and one mar-

keting scholar reviewed the instrument. As a pre-test,

the questionnaires were discussed in focus-group

interviews of 15 people (some of them had used M-

Internet before and others had not). Feedback was

obtained about the length of the instrument, the format

of the scales, content, and question ambiguity. In

addition, the respondents were asked to identify fac-

tors not in the questionnaire that they considered

important and to describe their judgment related to

the use of M-Internet. The final list of items for each

construct reflects the feedback received, and it is

provided in Appendix A.

Empirical data for this study was collected via an

Internet survey. Messages advertising the survey were

posted for 2 weeks at public forums. At the same time,

emails were sent out via the university emailing list to

all the undergraduates and graduates of a major uni-

versity in Singapore. In Singapore, there are 78 mo-

bile phone subscribers per 100 inhabitants [37]. About

60% of M-Internet users are between 20 and 34 years

old [13]. For this reason, Singapore is a good context

for M-Internet study. Each of the respondents was

paid $5 as an incentive. Potential respondents were

reminded not to take the survey if they had no expe-

rience in using M-Internet or were regular users of M-

Internet. The respondents were also requested to enter

their mobile phone numbers for accessing M-Internet,

so that we could check if they had M-Internet expe-

rience. In total, 161 responses were usable. Most of

the participants had only trial experiences (1 to 4

times in total). With only limited M-Internet experi-

ence, these respondents were appropriate for adoption

study. Detailed descriptive statistics of the respon-

dents’ characteristics are shown in Table 2. Out of

the three services offered by M-Internet, contents (i.e.,

Table 4

Correlation analysis between the variables

INT VAL USE ENJ TECH

VAL 0.599**

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126 119

games and news) and commerce (i.e., ticketing and

shopping) services emerged as the two most frequent-

ly tried services followed by communication (i.e.,

mobile email) services.

USE 0.342** 0.402**

ENJ 0.357** 0.418** .502**

TECH 0.311** 0.406** .489** 0.519**

FEE �0.271** �0.406** � .114 �0.116 �0.108INT: adoption intention, VAL: perceived value, USE: usefulness

ENJ: enjoyment, TECH: technicality, FEE: perceived fee.

** p V 0.01.

5. Data analysis and results

5.1. Reliability and validity of instruments

The means, standard deviations and reliabilities of

all perceptual research variables are summarized in

Table 3. The scales show good reliability with Cron-

bach’s alphas N0.7. We also conducted principal com-

ponent factor analysis on the four independent

variables and one dependent variable (perceived

value) with VARIMAX rotation as in Appendix B.

A total of five factors with eigenvalue greater than 1.0

were identified. All items of the variables loaded on

each distinct factor and explained 72.7% of the total

variance. Most variables showed convergent validity

with factor loadings above 0.6 except the fourth item

of technicality (TECH4). Because of the low factor

loading (0.357), TECH4 was excluded from further

analysis. When compared across factors, the items

were loaded highest on their own factors. Therefore,

with the exception of TECH4, the results of the factor

analysis indicate that the conditions of convergent and

discriminate validity were satisfactorily met.

5.2. Hypothesis test

We conducted a Pearson correlation analysis. Pear-

son correlation was calculated for the variables mea-

sured by interval or ratio scales. The simple

correlations among all the research variables are

shown in Table 4. The regression model was further

Table 3

Reliability and descriptive statistics

Variable Reliability Mean Standard deviation

Adoption intention 0.83 4.37 1.11

Perceived value 0.87 4.23 1.03

Usefulness 0.95 4.38 1.05

Enjoyment 0.84 4.53 1.02

Technicality 0.76 4.25 0.95

Perceived fee 0.89 4.63 1.23

,

tested for multicollinearity by examination of the

collinearity statistics, the variance inflation factor

(VIF) and tolerance. As a rule of thumb, if the VIF

of a variable exceeds 10, that variable is said to be

highly collinear and will pose a problem to regression

analysis [26]. Although several variables showed sig-

nificant correlations, their tolerance values ranged

from 0.624 to 0.833 and VIF values ranged from

1.201 to 1.600, indicating that multicollinearity is

not a likely threat to the parameter estimates in our

study.

Fig. 2 shows the results of the multiple regression

analyses. First, perceived value (b =0.599, p b0.001)

is significantly related to adoption intention (R2=

0.359). Thus, H1 is supported. Next, the four factors

are found to be significantly related to perceived value

(R2=0.365): usefulness (b =0.176, p b0.05), enjoy-

ment (b =0.196, p b0.05), technicality (b =0.181,

pb0.05), and perceived fee (b =�0.343, p b0.001).

Thus, H2, H3, H4 and H5 are all supported.

An additional test was conducted to examine

the direct effects of the five antecedents including

perceived value on adoption intention. The result

indicates perceived value is significant at p b0.001

level (b =0.410). However, all the other four ante-

cedents are not significant: usefulness (b =0.080,

p=0.309), enjoyment (b =0.094, p =0.243), techni-

cality (b =0.014, p =0.864), and perceived fee

(b =�0.045, p =0.309522). Further, we had expected

that perceived value might mediate the relationship

between the antecedents and adoption intention be-

cause perceived value reflects the overall comparison

between cost and benefit in the use of M-Internet.

We tested the mediating relationship additionally

using the mediating-effect test method [8,10] as in

Table 5. The results support our expectation that per-

PerceivedValue

Benefit

Sacrifice

Usefulness

Technicality

Perceived Fee

Enjoyment

AdoptionIntention

0.599***

0.176*

(R2 = 0.365) (R2 = 0.359)

0.196*

-0.343***

0.181*

Fig. 2. Hypothesis testing results.

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126120

ceived value fully mediates the relationship between

the four antecedents (usefulness, enjoyment, technical-

ity, and perceived fee) and adoption intention.

6. Discussion

The results support the validity of our research

model, VAM. VAM asserts that M-Internet adoption

is determined by perceptions of the value of M-Inter-

net and these in turn are determined by the perceptions

of the usefulness, enjoyment, fee and technicality of

M-Internet. The results support all five hypotheses,

Table 5

Testing the mediating effect of perceived value

Step Dependent

variables

Independent variables F R2

Variable b

1.1 VAL USE 0.402*** 30.376*** 0.161

1.2 INT USE 0.341*** 20.819*** 0.116

1.3 INT USE 0.120 46.229*** 0.371

VAL 0.551***

2.1 VAL ENJ 0.418*** 33.668*** 0.175

2.2 INT ENJ 0.357*** 23.252*** 0.128

2.3 INT ENJ 0.129 46.973*** 0.373

VAL 0.545***

3.1 VAL TECH 0.436*** 37.316*** 0.190

3.2 INT TECH 0.299*** 15.563*** 0.089

3.3 INT TECH 0.046 44.594*** 0.361

VAL 0.579***

4.1 VAL FEE �0.406*** 31.356*** 0.165

4.2 INT FEE �0.271*** 12.576** 0.073

4.3 INT FEE �0.033 44.437*** 0.360

VAL 0.586***

** pV 0.01.

*** pV 0.001.

suggesting that extrinsic and intrinsic benefits prompt

customers’ intention to adopt M-Internet while mon-

etary costs and non-monetary costs serve as barriers to

adoption. The results also suggest that the perceived

value of M-Internet is not only inferred by cognitive

elements such as usefulness and fee, but also enjoy-

ment, an affective element.

Perceived sacrifices (perceived fee and technicali-

ty) seem to have greater impact than perceived bene-

fits (usefulness, enjoyment) on perceived value. A

regression of perceived value with benefit constructs

alone shows an R2 of 0.224, while a regression with

sacrifice constructs alone shows a higher R2 of 0.297.

(Each construct alone shows lower R2, ranging from

0.162 to 0.175.) This is consistent with the endow-

ment effect of the prospect theory [31], which means

blosses loom larger than gainsQ. Customers are de-

terred more by costs than they are attracted by bene-

fits. Since M-Internet is a fairly new technology,

customers will not risk committing time, effort and

money to it without having some assurance of its

benefits. Even if customers recognize that M-Internet

is beneficial, they may still not find it valuable unless

they perceive the sacrifices to be less than the benefits

they receive.

In line with previous studies [22,25], our finding

suggests that perceived fee exerts a strongly signif-

icant effect on perceived value. Investing money in

an unfamiliar technology entails risk such as in

performance failure, and the higher the perceived

fee and hence risk, the more reluctant customers

are to adopt the technology. Similarly, consumer

surveys have found that a high price or having to

pay a price at all keeps many new customers from

trying services they are not sure about [3]. Monetary

Usefulness

Intention

Ease of Use

0.269***

0.142** (R2 = 0.131)

Fig. 3. Testing results of TAM.

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126 121

sacrifice therefore reduces the perceived value of

mobile services.

Technicality is a construct specific to M-Internet

and introduced in VAM. New users are concerned

about the technicality of M-Internet because it trans-

lates into the amount of time and effort required to

learn and use the system. The major advantage offered

by M-Internet is convenience, creation of new free-

dom, and ubiquity [2]. However, if its use involves

complex manipulation, navigation, slow response,

elaborate connection procedures and/or, inconsistent

availability, then its advantage would be weakened.

Under such conditions, customers would take into

account the technicality of M-Internet when forming

opinions of its value. Our finding is consistent with

the research of Venkatesh et al. [56], which found that

effort-oriented constructs are more salient in the early

stages of adoption when process issues represent hur-

dles to be overcome.

In accordance with motivation research, we have

established that customers are extrinsically and in-

trinsically motivated to adopt M-Internet. Enjoyment

is, as expected, an intrinsic motivator and an affec-

tive determinant of perceived value. Like previous

studies on adoption, usefulness has emerged as one

of the major factors determining adoption, and in

our case, through perceived value. What distin-

guishes our results from related prior studies (e.g.,

[15,16,32]) is that usefulness is not the top concern

for M-Internet adopters. One possible reason is that

customers could perceive M-Internet as a substitute

for stationary Internet when they are on the move,

using it primarily for convenience or due to a lack

of alternatives. Customers do consider the useful-

ness of M-Internet because they would not adopt a

technology that does not fulfill their needs nor

qualify as an alternative to stationary Internet; M-

Internet must therefore provide many services that

are provided by stationary Internet. However, when

choosing between stationary Internet and M-Internet

to access a particular service available on both

channels, the consumer would already have deemed

the service useful, and other factors such as techni-

cal service quality and usage fee therefore become

significant.

The crux of VAM is the value construct, which

is postulated to predict adoption intention. Our

results show that perceived value has a significant

effect (b =0.539, p b0.001) on adoption intention,

evidently supporting our VAM concept. Further-

more, it fully mediates the effects of usefulness,

enjoyment, technicality and perceived fee on adop-

tion intention. This is consistent with the prior

research on perceived value which has recurrently

verified perceived value as a predictor of intention

(e.g. [11]). This result also justifies our classifica-

tion of each antecedent of perceived value as a

benefit or sacrifice component, i.e., it is reasonable

that perceived usefulness and enjoyment are benefit

components while technicality and perceived fee are

sacrifice components.

The proposed VAM can also be compared with

TAM. TAM has two independent variables (useful-

ness and ease of use) and one dependent variable

(adoption intention). To make this comparison, we

collected additional data from the subjects. While

the two variables, usefulness and adoption intention,

are common both for VAM and TAM, ease of use

needs different measurement items. We adapted the

items from Davis [15] as in Appendix A. While VAM

could explain 35.9% of the variance in adoption in-

tention, TAM could explain a much lower 13.1% of

the variance (Fig. 3).

Nevertheless, there are limitations in this study

which may restrict the generalizability of the findings,

and these could be addressed in future studies. First,

about 50% of our subjects were undergraduate and

graduate students. Although these respondents were

between 20 and 30 years old–the range with the most

potential M-Internet adopters–they might be con-

strained by monetary and cost issues more than

those holding jobs and drawing a steady income.

Second, data collection was geographically limited

to Singapore. As M-Internet adoption is a worldwide

phenomenon, replication of the findings across differ-

ent geographical contexts is necessary. Future studies

could perhaps be cross-national.

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126122

7. Implications

From a theoretical point of view, this research has

served to broaden our understanding of the factors

influencing new technology adoption from the per-

spective of customers; it is a response to the call for

more in-depth, customer-oriented research in M-Inter-

net services. The main theoretical contribution of this

research is the development of the Value-based Adop-

tion Model of Technology (VAM). VAM is particu-

larly useful for understanding the adoption of M-

Internet in comparison with TAM as it examines the

adoption of M-Internet as a new ICT by individuals

playing the double roles of service consumer and

technology user. As discussed in Introduction, adop-

tion of traditional technologies for work purposes in

organizational settings is different from the adoption

of new ICT for personal purposes in non-organiza-

tional settings. While TAM could explain the adoption

of traditional technologies by users in organizational

settings, it has its limitations in explaining the adop-

tion of new ICT like M-Internet by customers because

customer choice and behavior are mainly determined

by value of the choice object, as exemplified in eco-

nomics [31,40] and marketing research [52,61]. Our

comparison between TAM and VAM shows that VAM

is more effective than TAM in explaining customer

adoption of M-Internet.

In addition, this study has shown the importance

of perceived value in explaining the adoption of M-

Internet by customers. Perceived value fully mediates

the effects of customers’ beliefs on adoption inten-

tion, which conforms to value research in the eco-

nomics and marketing literature. Prior to our study,

technology adoption models have not investigated the

role of perceived value in determining adoption. This

study is the first empirical effort to examine the

impact of perceived value in concert with technology

adoption. Meanwhile, the marketing literature has

focused on the value of a product (goods and/or

services) in relation to purchase intention. Our re-

search serves to bridge this gap and expand the

perceived value literature.

This study also provides a different view of the

two major determinants of technology adoption:

usefulness and ease of use (closely related to tech-

nicality in this study). Contrary to prior research

findings [15,16], the effect of perceived usefulness

on adoption intention is not direct but operates

indirectly through perceived value. Technicality

also operates indirectly through perceived value

on adoption intention. Moreover, the impact of

perceived usefulness on perceived value is also

not the strongest among the four antecedents. Sac-

rifice components (perceived fee and technicality)

seem to have greater effects on perceived value

than benefit components (usefulness and enjoyment)

do. In turn, perceived value dominantly determines

adoption intention.

This study further provides practical implications

for the development, design and marketing of M-

Internet. Since potential adopters are concerned

about both costs and benefits when assessing the

value of M-Internet, effort has to be put into

creating an impression of low costs and desirable

benefits so that customers will consequently place a

higher value on M-Internet. As has been illustrated

in our research, higher perceived value indicates

greater willingness to adopt the technology. We

have also gained important insights on the relative

importance of costs and benefits in determining

value. Consistent with previous research [31,52],

the results of this study imply that perceived

costs affect customers’ evaluation of the value of

M-Internet more than the benefits to be derived.

Improvement in customers’ perception of costs

would be the most important driver of M-Internet

adoption.

Costs can be minimized by lowering usage fee

and/or improving the technical quality of M-Internet.

Potential adopters of M-Internet are found to be

sensitive to cost, given that their adoption decision

is largely dependent on perceived value. M-Internet

providers may want to offer customers free trials of

the service to allow them to familiarize themselves

with it since customers would not pay for something

that they know little about. Also, M-Internet provi-

ders may want to review the fee structure for service

utilization. In terms of technical quality, customers

have the highest expectations for reliability, connec-

tivity, response time and ease of use. It is imperative

for developers to put in further effort to address

these issues.

The appeal of benefits also plays a part in increas-

ing the value perceived by customers and should not

be neglected in the development of new functions and

Variable Item Description Reference

Adoption

intention

INT1 I plan to use M-Internet

in the future

Davis

et al. [16]

INT2 I intend to use

M-Internet in the future

INT3 I predict I would use

M-Internet in the future

Perceived

value

VAL1 Compared to the fee

I need to pay, the use

of M-Internet

Sirdeshmukh

et al. [46]

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126 123

the enhancement of design features. Customers are

motivated not only by extrinsic benefits but also the

intrinsic outcomes of using M-Internet. Rather than

creating services based on experts’ perception of use-

fulness and demand, developers should conduct reg-

ular market research to discover consumer needs and

wants and transform the findings into services useful

to consumers. Although enjoyment seems to have the

least influence on perceived value, developers should

nonetheless strive to include the fun element into

services because customers would still prefer enjoy-

able and entertaining services.

offers value for money

VAL2 Compared to the effort

I need to put in, the use of

M-Internet is beneficial to me

VAL3 Compared to the time

I need to spend, the

use of M-Internet is

worthwhile to me

VAL4 Overall, the use of

M-Internet delivers me

good value

Usefulness USE1 Using M-Internet enables

me to accomplish tasks

more quickly

Davis [15]

USE2 Using M-Internet

enhances my task

effectiveness

USE3 Using M-Internet makes

it easier to do my task

USE4 Using M-Internet

improves my task

performance

USE5 Using M-Internet saves

me time and effort in

performing tasks

USE6 M-Internet is useful in

performing my task

Enjoyment ENJ1 I have fun interacting

with M-Internet

Agarwal and

Karahanna

ENJ2 Using M-Internet

provides me with a lot

of enjoyment

[1]

ENJ3 I enjoy using M-Internet

ENJ4 Using M-Internet bores

me (reversed)

Perceived

fee

FEE1 The fee that I have

to pay for the use of

M-Internet is too high

Voss et al.

[58]

FEE2 The fee that I have to

pay for the use of

M-Internet is

reasonable (reversed)

(continued on next page )

8. Conclusion

This study has discussed the difficulties in explain-

ing the adoption of new ICT by individuals who play

the dual roles of service consumer and technology

user for personal purposes with the well known Tech-

nology Adoption Model (TAM). By adopting the

theory of consumer choice in the economics and

marketing traditions, we have developed the Value-

based Adoption Model (VAM) to explain technology

adoption where the users are also playing as consu-

mers. The model is applied to study the adoption of

M-Internet by individual customers. VAM offers a

clear understanding of what factors influence value

perception and how value perception leads to adoption

from the value maximization perspective. This study

has found that value perception is a major determinant

of M-Internet adoption by testing the mediating effect

of perceived value on the relationship between a

customer’s benefit and sacrifice related beliefs and

the customer’s adoption intention. As perceived

value is a prominent factor in understanding M-Inter-

net adoption, a suitably packaged M-Internet service

which maximizes perceived value from the benefit and

sacrifice perspective will accelerate M-Internet adop-

tion. Adoption of M-Internet is a prerequisite for the

adoption and proliferation of M-Commerce. Thus, our

study on M-Internet adoption is an initial step toward

understanding customer behavior in M-Commerce.

We hope our findings will encourage further research

and more in-depth and extensive analyses to demysti-

fy the driving forces of M-Commerce. This will be

beneficial to academic researchers, practitioners and

users alike.

Appendix A. Operationalization of the model

variables

Appendix A (continued)

Variable Item Description Reference

Perceived

fee

FEE3 I am pleased with the

fee that I have to pay

for the use of M-Internet

(reversed)

Technicality TECH1 It is easy to use

M-Internet

Davis [15];

DeLone and

TECH2 M-Internet can be

connected instantly

McLean [19]

TECH3 M-Internet takes a

short time to respond

TECH4 It is easy to get

M-Internet to do what

I want it to do

TECH5 The system of M-Internet

is reliable

Ease of use EOU1 It is easy to use

M-Internet

Davis [15]

EOU2 It is easy to get

M-Internet to do what

I want it to do

EOU3 It is convenient to

access M-Internet

H.-W. Kim et al. / Decision Support Systems 43 (2007) 111–126124

Appendix B. Factor analysis results

1 2 3 4 5

VAL1 0.032 0.628 �0.047 0.208 0.429

VAL2 0.173 0.856 0.177 0.051 0.091

VAL3 0.194 0.759 0.271 0.199 0.129

VAL4 0.267 0.825 0.107 0.163 0.203

USE1 0.819 0.054 0.237 0.171 0.061

USE2 0.872 0.111 0.199 0.180 0.012

USE3 0.903 0.169 0.090 0.118 0.018

USE4 0.883 0.073 0.104 0.186 0.064

USE5 0.795 0.190 0.199 0.204 0.063

USE6 0.794 0.236 0.133 0.164 �0.005ENJ1 0.231 0.130 0.302 0.779 0.037

ENJ2 0.246 0.030 0.200 0.820 0.097

ENJ3 0.347 0.113 0.300 0.761 0.028

ENJ4 �0.103 �0.349 0.029 �0.602 0.038

FEE1 �0.009 �0.230 0.061 0.067 �0.856FEE2 0.028 0.097 0.098 �0.002 0.922

FEE3 0.087 0.125 0.010 0.124 0.888

TECH1 0.270 0.041 0.730 0.166 �0.012TECH2 0.207 0.214 0.727 0.214 0.014

TECH3 0.006 �0.003 0.757 0.143 0.024

TECH4 0.321 0.291 0.357 �0.225 0.047

TECH5 0.280 0.240 0.662 0.138 �0.001Eigenvalue 8.117 3.008 1.945 1.513 1.409

% of variance 36.895 13.672 8.843 6.899 6.405

Cumulative % 36.895 50.566 59.409 66.289 72.694

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Hee-Woong Kim is an assistant professor in the School of Com-

puting at the National University of Singapore. He was invited to

the ICIS doctoral consortium (1997) and worked as a post-doctoral

fellow in the Sloan School of Management at Massachusetts Insti-

tute of Technology. His current research focuses on value-driven

customer behavior and post-adoption of IT.

Hock Chuan Chan is an associate professor at the Department of

Information Systems, National University of Singapore. He has a

BA from the University of Cambridge and a PhD from the Univer-

sity of British Columbia, Canada. His current research focuses on

user–database interaction, information systems acceptance and

spreadsheet model visualization.

Sumeet Gupta is currently a PhD Student at the Department of

Information Systems (School of Computing) in the National Uni-

versity of Singapore. He graduated with an MBA at the NUS

Business School from the National University of Singapore. His

research interests are in e-commerce with specific focus on IT post-

adoption, Internet Shopping and Virtual Communities. He has

published in conferences, namely ICIS and AMCIS.